滑块验证码

# -*- coding: utf-8 -*-
import numpy as np
import random
from selenium.webdriver import ActionChains
import time
from selenium import webdriver
from PIL import Image
import os
from selenium.webdriver.support.ui import WebDriverWait
# opencv-python需要安装这个模块
import cv2


class Login(object):
    """
    腾讯防水墙滑动验证码破解
    使用OpenCV库
    成功率大概90%左右：在实际应用中，登录后可判断当前页面是否有登录成功才会出现的信息：比如用户名等。循环
    https://open.captcha.qq.com/online.html
    破解 腾讯滑动验证码
    腾讯防水墙
    python + seleniuum + cv2
    """
    def __init__(self):
        # 如果是实际应用中，可在此处账号和密码
        self.url = "https://open.captcha.qq.com/online.html"
        self.driver = webdriver.Chrome()

    @staticmethod
    def show(name):
        cv2.imshow('Show', name)
        cv2.waitKey(0)
        cv2.destroyAllWindows()

    @staticmethod
    def webdriverwait_send_keys(dri, element, value):
        """
        显示等待输入
        :param dri: driver
        :param element:
        :param value:
        :return:
        """
        WebDriverWait(dri, 10, 5).until(lambda dr: element).send_keys(value)

    @staticmethod
    def webdriverwait_click(dri, element):
        """
        显示等待 click
        :param dri: driver
        :param element:
        :return:
        """
        WebDriverWait(dri, 10, 5).until(lambda dr: element).click()

    @staticmethod
    def get_postion(chunk, canves):
        """
        判断缺口位置
        :param chunk: 缺口图片是原图
        :param canves:
        :return: 位置 x, y
        """
        otemp = chunk
        oblk = canves
        target = cv2.imread(otemp, 0)
        template = cv2.imread(oblk, 0)
        # w, h = target.shape[::-1]
        temp = 'temp.jpg'
        targ = 'targ.jpg'
        cv2.imwrite(temp, template)
        cv2.imwrite(targ, target)
        target = cv2.imread(targ)
        target = cv2.cvtColor(target, cv2.COLOR_BGR2GRAY)
        target = abs(255 - target)
        cv2.imwrite(targ, target)
        target = cv2.imread(targ)
        template = cv2.imread(temp)
        result = cv2.matchTemplate(target, template, cv2.TM_CCOEFF_NORMED)
        x, y = np.unravel_index(result.argmax(), result.shape)
        return x, y
        # # 展示圈出来的区域
        # cv2.rectangle(template, (y, x), (y + w, x + h), (7, 249, 151), 2)
        # cv2.imwrite("yuantu.jpg", template)
        # show(template)

    @staticmethod
    def get_track(distance):
        """
        模拟轨迹 假装是人在操作
        :param distance:
        :return:
        """
        # 初速度
        v = 0
        # 单位时间为0.2s来统计轨迹，轨迹即0.2内的位移
        t = 0.2
        # 位移/轨迹列表，列表内的一个元素代表0.2s的位移
        tracks = []
        # 当前的位移
        current = 0
        # 到达mid值开始减速
        mid = distance * 7 / 8

        distance += 10  # 先滑过一点，最后再反着滑动回来
        # a = random.randint(1,3)
        while current < distance:
            if current < mid:
                # 加速度越小，单位时间的位移越小,模拟的轨迹就越多越详细
                a = random.randint(2, 4)  # 加速运动
            else:
                a = -random.randint(3, 5)  # 减速运动

            # 初速度
            v0 = v
            # 0.2秒时间内的位移
            s = v0 * t + 0.5 * a * (t ** 2)
            # 当前的位置
            current += s
            # 添加到轨迹列表
            tracks.append(round(s))

            # 速度已经达到v,该速度作为下次的初速度
            v = v0 + a * t

        # 反着滑动到大概准确位置
        for i in range(4):
            tracks.append(-random.randint(2, 3))
        for i in range(4):
            tracks.append(-random.randint(1, 3))
        return tracks

    @staticmethod
    def urllib_download(imgurl, imgsavepath):
        """
        下载图片
        :param imgurl: 图片url
        :param imgsavepath: 存放地址
        :return:
        """
        from urllib.request import urlretrieve
        urlretrieve(imgurl, imgsavepath)

    def after_quit(self):
        """
        关闭浏览器
        :return:
        """
        self.driver.quit()

    def login_main(self):
        # ssl._create_default_https_context = ssl._create_unverified_context
        driver = self.driver
        driver.maximize_window()
        driver.get(self.url)

        click_keyi_username = driver.find_element_by_xpath("//div[@class='wp-onb-tit']/a[text()='可疑用户']")
        self.webdriverwait_click(driver, click_keyi_username)

        login_button = driver.find_element_by_id('code')
        self.webdriverwait_click(driver, login_button)
        time.sleep(1)

        driver.switch_to.frame(driver.find_element_by_id('tcaptcha_iframe'))  # switch 到 滑块frame
        time.sleep(0.5)
        bk_block = driver.find_element_by_xpath('//img[@id="slideBg"]')  # 大图
        web_image_width = bk_block.size
        web_image_width = web_image_width['width']
        bk_block_x = bk_block.location['x']

        slide_block = driver.find_element_by_xpath('//img[@id="slideBlock"]')  # 小滑块
        slide_block_x = slide_block.location['x']

        bk_block = driver.find_element_by_xpath('//img[@id="slideBg"]').get_attribute('src')       # 大图 url
        slide_block = driver.find_element_by_xpath('//img[@id="slideBlock"]').get_attribute('src')  # 小滑块 图片url
        slid_ing = driver.find_element_by_xpath('//div[@id="tcaptcha_drag_thumb"]')  # 滑块

        os.makedirs('./image/', exist_ok=True)
        self.urllib_download(bk_block, './image/bkBlock.png')
        self.urllib_download(slide_block, './image/slideBlock.png')
        time.sleep(0.5)
        img_bkblock = Image.open('./image/bkBlock.png')
        real_width = img_bkblock.size[0]
        width_scale = float(real_width) / float(web_image_width)
        position = self.get_postion('./image/bkBlock.png', './image/slideBlock.png')
        real_position = position[1] / width_scale
        real_position = real_position - (slide_block_x - bk_block_x)
        track_list = self.get_track(real_position + 4)

        ActionChains(driver).click_and_hold(on_element=slid_ing).perform()  # 点击鼠标左键，按住不放
        time.sleep(0.2)
        # print('第二步,拖动元素')
        for track in track_list:
            ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()  # 鼠标移动到距离当前位置（x,y）
            time.sleep(0.002)
        # ActionChains(driver).move_by_offset(xoffset=-random.randint(0, 1), yoffset=0).perform()   # 微调，根据实际情况微调
        time.sleep(1)
        # print('第三步,释放鼠标')
        ActionChains(driver).release(on_element=slid_ing).perform()
        time.sleep(1)

        print('登录成功')
        self.after_quit()


if __name__ == '__main__':
    phone = "****"
    login = Login()
    login.login_main()